journal of business and technical power and authority ª ... · mapping. this article theorizes...

Power and Authorityin Disease Maps:Visualizing MedicalCartographyThrough YellowFever Mapping

Candice A. Welhausen1

AbstractMedical cartography became an important data visualization tool in the19th century. In this article, the author argues that early yellow fevermaps invoked power and authority over diseased space through theirvisual conventions and scientific authority as statistical graphics as wellas by visually reinforcing underlying Western ideologies about disease,illness, and health. Further, the creation of these maps established avisual precedent for invoking this authority that continues today. Aspublic health continues to move toward a global health perspective inthe 21st century, understanding how mapping constructs and shapesknowledge about disease, illness, and health will become increasinglyimportant.

1Department of English, University of Delaware, Newark, DE, USA

Corresponding Author:

Candice A. Welhausen, Department of English, University of Delaware, 203 Memorial Hall,

Newark, DE 19716, USA.

E-mail: [email protected]

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Keywordsvisual rhetoric, medical cartography, yellow fever, Western medicine, dis-ease mapping

The origins of data visualization can be traced back to antiquity, when early

maps and drawings were created primarily for navigational purposes (see

Friendly, 2008; Friendly & Denis, 2006). The statistical graphics that we

recognize today evolved more recently, however, after the discovery of

probability theory in the mid-17th century and interest grew in gathering

a range of data—demographic, economic, social, environmental, and moral

(see Beniger & Robyn, 1978; Friendly, 2008; Friendly & Denis, 2006; Funk-

houser, 1937). As the collection of this ‘‘political arithmetic,’’ as 17th century

economist and physician William Petty (cited in Friendly, 2008, p. 505)

characterized it, began to proliferate throughout the late 18th and early to

mid-19th centuries, so did the creation of visual forms used to display, shape,

and interpret this information.

This more recent history of data visualization that began in the 17th

century reflects the move toward ‘‘visual thinking’’ (Friendly & Denis,

2006, p. 1) during which the purpose of collecting quantitative informa-

tion moved from a focus on description to constructing generalizable

visual knowledge that could be used to draw inferences and solve prob-

lems. In the emerging modern-day fields of public health and epidemiol-

ogy, early medical cartography became a particularly significant data

visualization tool in the first half of the 19th century as officials struggled

to control the disease outbreaks that had become increasingly common.

Fueled by rapidly growing urban populations, poor sanitation, and limited

knowledge of the true causes of disease transmission, illnesses such as

cholera and yellow fever spread across the United States and Europe.

As these diseases became endemic, early medical cartographers, who

were also often physicians, began investigating their causes and produced

reports that made both visual (in the form of maps and other statistical gra-

phics) and verbal arguments that attempted to identify causal factors.

English physician John Snow’s 1854 map of a cholera outbreak in Lon-

don’s Golden Square district, for instance, illustrates a well-known example

of this trend (see Figure 1). The now famous map is often credited with

revealing the true cause of the outbreak, the contaminated water from the

Broad Street pump, which then led to the quick removal of the pump’s han-

dle. In reality, the historical account is more complex (see Brody, Vinten-

Johansen, Paneth, & Rip, 1999), and Snow’s contributions to public health

2 Journal of Business and Technical Communication



and epidemiology would not be formally recognized until new attention was

called to his work in the 1930s (see Vandenbroucke, Eelkman, & Beukers,

1991). The Broad Street event endures in the ‘‘folklore of public health and

epidemiology’’ (Brody, Rip, Vinten-Johansen, Paneth, & Rachman, 2000,

p. 64) today, in part, because Snow’s story invokes a powerful narrative

of scientific progress (McLeod, 2000). We remember Snow because he was

right about the pump and, more important, because he was right about cho-

lera. But we also remember Snow because the Broad Street map constructs

a powerful visual argument about how disease—in this case, cholera—is

situated within a particular time, space, and place.

The notion that maps act rhetorically to advance power relationships has

been well theorized in the fields of technical communication (see Barton &

Barton, 1993; Propen, 2007, 2012), geography (see Monmonier, 1995), and

critical cartography (see Crampton, 2010; Harley, 2009; Pickles, 2004;

Wood, 1992), which offers a framework for investigating the ways that

maps ‘‘link geographic knowledge with power’’ (Crampton & Krygier,

Figure 1. Snow’s (1855) map of the 1854 outbreak in Golden Square.Source: Courtesy of the Historical Medical Library of the College of Physicians ofPhiladelphia.

Welhausen 3



2006, p. 11) and construct social and cultural knowledge (see Harley, 2002;

Monmonier, 1995; Turnbull, 1989; Wood, 1992). At the same time, these

relationships have not been well explored within the context of disease

mapping.

This article theorizes early medical cartography through this perspective

and discusses its implications for contemporary disease mapping as a data

visualization tool in the field of public health and epidemiology. Using four

historic yellow fever maps created in the United States during the late 18th

through the mid-19th centuries as examples, I argue that early disease maps

invoked power and authority through their visual conventions and scientific

authority as statistical graphics and by visually reinforcing underlying

Western values about health, disease, and illness. These trends can still

be seen today, which I illustrate by discussing a contemporary yellow fever

map that shows areas still at risk for the disease in Africa.

Further, while Western medicine has been criticized for decontextualiz-

ing and mechanizing the human experience of disease, I suggest that the

ideologies that undergird this perspective were critical in facilitating a

population-based understanding of disease prevention, which led, in part,

to the emergence of the modern-day disciplines of public health and epide-

miology. As public health increasingly moves toward a global health per-

spective in the 21st century and digital mapping tools such as geographic

information systems become a primary methodology for addressing public

health problems, understanding how maps construct and shape knowledge

about disease, illness, and health will become increasingly important.

Yellow Fever and Early Medical Cartography: VisuallyConstructing Power and Authority

Today yellow fever is no longer a significant public health concern in most

parts of the world. But this disease, along with waterborne illnesses such as

cholera, posed a significant threat in the United States and Europe through-

out the 19th century. Transmitted through the bite of mosquitoes infected

with the yellow fever virus, the disease is believed to have arrived in

North America on West African slave ships in the mid-17th century

(Rogers, Wilson, Hay, & Graham, 2006; see also Blake, 1968).

Throughout the 18th and 19th centuries, epidemics swept major U.S.

port cities such as New York and Philadelphia (see Blake, 1968; Foster,

Jenkins, & Toogood, 1998; Koch, 2011).

Yellow fever presents a strong opportunity to explore historic as well as

contemporary disease mapping from a critical cartography perspective




because mapping this disease spans the history of medical cartography.

Two of the oldest surviving disease maps were created by Seaman (1798)

to document a yellow fever outbreak in the New York harbor area while

Pascalis (1819) created a map documenting another outbreak in a neighbor-

ing area over 20 years later. In the mid-19th century, Jewell (1853) and

Barton (1857) mapped outbreaks near the South Street Wharf area in

Philadelphia and in New Orleans, respectively. Finally, as recently as

2011, a map, published on the Centers for Disease Control and Prevention

(CDC) website (Jentes et al., 2011), shows at-risk tropical areas in Africa

where the disease remains endemic (World Health Organization, 2008).

The first thematic maps are believed to originate in the late 1700s (see

Friendly & Denis, 2006; Funkhouser, 1937; Robinson, 1982), following

significant advances in the field of cartography throughout the 15th cen-

tury—specifically, the invention of new printing capabilities and an

increasing emphasis on more realistic geographic depictions (see Robinson,

1982). The exact origins of medical cartography, however, are difficult to

pinpoint. Several scholars have pointed to the wave of cholera epidemics

that began to sweep Europe in the 1830s (Gilbert, 1958; Jarcho, 1970;

Robinson, 1982). But Stevenson’s (1965) historical work on late 18th-

century ‘‘spot’’ maps, which discusses the early yellow fever maps created

by Seaman (1798), Pascalis (1819), and Barton (1857), and Koch’s (2005)

analysis of a 1694 plague map of Bari, Italy (previously identified by Jarcho,

1970), suggest an earlier time frame. Koch (2005) speculated that more dis-

ease maps were probably created in the 1600s and early 1700s, but none have

survived to the present day (see also Koch, 2011; Robinson, 1982).

In all likelihood, the first disease maps are contemporaneous with the

statistical graphics that emerged in the 17th century. The practice of disease

mapping, in fact, may have originated in attempts to resolve the ongoing

dispute between the two dominant theories of disease transmission at the

time, that is, contagion and anticontagion (Stevenson, 1965).

Prior to the discovery of microbiology in the late 19th century, the actual

causes of communicable and infectious disease transmission were

unknown. Some diseases (e.g., smallpox, scarlet fever, and measles, see

Mitman & Numbers, 2003, p. 393) were believed to be contagious. That

is, they spread through person-to-person contact. Anticontagionists, how-

ever, argued that diseases such as cholera and yellow fever were not conta-

gious and instead spread through miasma (Smith, 1993), essentially

exposure to ‘‘bad air’’ (Mitman & Numbers, 2003, p. 394). No one under-

stood exactly how miasma developed. Yet common belief held that the

smell of rotting organic matter combined with certain weather conditions

Welhausen 5



(usually heat and humidity) resulted in a ‘‘putrid effluvia,’’ as Seaman

(1798, p. 331) described it.

After yellow fever arrived in the New World, researchers began to

observe that the disease seemed to prosper in warm, humid environments;

thus, tracking these conditions became particularly important to those

studying the disease (see Koch, 2011). Efforts to identify the specific envi-

ronmental variables that had prompted an outbreak can be seen in several of

the reports that accompanied the historic yellow fever maps discussed in

this article. Barton’s (1857) report, for instance, includes several detailed

tables reporting rainfall, level of humidity, temperature, and barometric

pressure. Jewell (1853) noted the direction of the wind several days after the

arrival of a ship, the Mandarin, at the South Street Wharf in Philadelphia.

The outbreak near this area occurred, Jewell argued, after the ship’s cargo

was unloaded and ‘‘noxious emanations which had been latent in the hold’’

were ‘‘acted upon by . . . heat and moisture . . . [which] poisoned the atmo-

sphere’’ (p. 12). Such reports sought to establish where the miasma was

likely to have originated or could develop in the future (as in Barton’s

1857 report) and to identify the exact environmental factors responsible.

For instance, an earlier investigation conducted by Barton (1834) also in

New Orleans offers the following assessment: ‘‘These winds uniformly

exasperated the yellow fever, and if they do so, they can surely tend to pro-

duce it’’ (p. 7). In Barton’s (1857) later report, which he created as a mem-

ber of a sanitary commission tasked with investigating conditions in the city

following another epidemic in New Orleans, his ‘‘sanitary map,’’ he

explained, shows areas where dirty water and ‘‘filth and garbage of all

kinds’’ were accumulating as well as areas with ‘‘low, crowded, and filthy

tenements,’’ which he claimed ‘‘are probably as disastrous in the production

of yellow fever’’ (p. ix).

Similarly, in his second map in his report (see Figure 2), Seaman (1798)

discussed polluted areas indicated by x and S symbols in the dock areas in

the lower right-hand corner. He stated, ‘‘Without the air of putrid effluvia,

they [the citizens of New York] need have no apprehension of a Yellow

Fever spreading among them’’ (p. 316).

In fact, many disease maps created throughout the 19th century sup-

ported the argument in favor of miasma because contagion, as Barrett

(1998) explained, was ‘‘not particularly geographic in nature’’ (p. 767). If a

disease spread through contact with an infected person, as contagionists

believed, then an epidemic of that disease should follow a pattern of ‘‘unending

diffusion of cases’’ (p. 767). Yet many early disease maps, such as those

created by Seaman (1798), Pascalis (1819), and Jewell (1853), revealed




patterns of spatial distribution that simply did not visually support contagion

but rather seemed to point to environmental factors such as miasma.

These early disease maps, like other statistical graphics, show relation-

ships between and among aggregate data, but they also simultaneously con-

struct temporal and spatial patterns of disease distribution. They showed

how yellow fever moved through space and time within a population during

an outbreak, visually linking cases with polluted areas and weather

Figure 2. Seaman’s (1798) second map (Plate 2).Source: National Library of Medicine, History of Medicine Division.

Welhausen 7



conditions to advance a theory of disease causation—usually miasma. In

this way, the creation of these maps demonstrates Koch’s (2005) observa-

tion that maps transform general knowledge into specific information. The

creators of these early yellow fever maps assembled information about the

conditions surrounding the outbreak—people affected, locations of cases,

and polluted areas—into concrete visual representations. Mapping is a form

of ‘‘abstract thinking,’’ Robinson (1982) explained, ‘‘a reduced, substitute

space for that of reality’’ (p. 1), and creating a map, as Koch (2005) stated,

‘‘encourages a perspective that is both relational and spatial at once’’ (p. 2).

In explaining how viewers construct meaning from maps, Robinson and

Petchenik (1976) suggested that maps link ‘‘knowledge and space’’ (p.

4). Maps depict a select moment in time, fusing abstract information and

dynamic, three-dimensional space into flattened, two-dimensional repre-

sentations that construct a particular version of reality that the map’s creator

can then use to advance a particular purpose.

The act of creating a map establishes metaphorical control and owner-

ship over the representation of the space shown in the map, transforming the

space into a thing—an object that can be studied and subsequently used for

some specific purpose, such as actions in the physical world, in terms of

navigating the space, making decisions about the space, or engaging in

other interactions with the space. Disease maps were created to identify the

factors that cause disease in order to effect action such as enacting quaran-

tine measures and sanitary reform, a movement that began in England in the

1830s (see Rosen, 1993, for a history of the sanitary reform movement). For

instance, Barton’s map, like other sanitary maps created in the early to mid-

19th century (see also Koch, 2005; Robinson, 1982), argued in favor of

cleaning up areas that might be prone to producing the dreaded disease-

causing miasma.

By the mid-19th century, the connection between epidemic disease and

poor environmental conditions was clear. Thus, many advocates of sanitary

reform, such as Barton, were more interested in identifying areas that posed

health risks than in finding the exact causes of specific outbreaks (see Brody

et al., 1999; Rosen, 1993). If overall sanitation were improved, then out-

breaks of diseases such as cholera and yellow fever could probably be

avoided entirely even if weather conditions favorable to miasma developed.

Barton’s (1857) report demonstrates this view in arguing for the ‘‘preven-

tion of moisture and the removal of filth’’ (p. 208) in areas that he identified

on the map (p. ix).

In shaping and defining geographic spaces in ways that allowed early

yellow fever researchers such as Barton to argue in favor of sanitary reform,




for instance, the creation of these early maps illustrates what Barton and

Barton (1993) referred to as ‘‘inclusion’’ and ‘‘exclusion’’ (p. 53), or

what Harley (2009) has termed ‘‘ideological filtering’’ (p. 138). That

is, the creation of these early maps demonstrates the ways that their

creators selected and framed visual information in ways that advanced

particular purposes.

Constructing Power and Authority Through VisualConventions

Early maps demonstrate inclusion and exclusion through their visual con-

ventions—more specifically, through perspective and the placement of

visual information. Constructing meaning from maps, like other forms of

visual communication, often ‘‘seems transparent [only] because we know

the [semiotic] code already’’ (Kress & van Leeuwen, 1996, p. 32) and

because visual communication follows particular conventions that readers

have come to expect (see Kostelnick & Hassett, 2003). Kress and van Leeu-

wen (1996) argued that the placement of visual information—top or bottom,

left or right, and center or margin, for instance—connotes particular mean-

ings. More specifically, in some interpretive contexts, information that

appears at the top is interpreted as ‘‘ideal’’ whereas information that appears

at the bottom is interpreted as ‘‘real’’ (pp. 186–187). Information at the cen-

ter is seen as the ‘‘nucleus’’ whereas information placed around the center is

seen as supportive (p. 196). In Western cultures, in particular, the placement

of visual information creates a hierarchy, conveying the level of importance

of each design element.

Most maps in Western cultures (with the exception of relatively recent

digital interfaces that allow users to see a street view), for instance, ‘‘look

down,’’ assuming an ‘‘aerial position of power,’’ as Kimball (2006) charac-

terized it (p. 378). Most maps also place north at the top, a convention that

Turnbull (1989) explained is ‘‘closely connected with the global rise and

economic dominance of northern Europe’’ (p. 8). The still-used Mercator

map, invented in 1569, has been criticized not only for its inaccurate depic-

tion of scale but also for its placement of Europe in the center (see Peters,

1974), which Harley (2009) suggested ‘‘must have contributed much to a

European sense of superiority’’ (p. 136).

In addition to perspective, Western maps also rely on metaphoric asso-

ciations related to size and shading (density). In Western cultures, bigger

usually implies better, and larger symbols have historically been used to

convey more important information (see also Harley, 2009). The use of

Welhausen 9



shading to indicate increasing density was established in 1826 (Friendly,

2008); this technique, also used by early cholera maps (Smith, 1993), has

now become conventional for showing less or more (density) of a particular

variable.

Many of these visual conventions (use of perspective and shading) can

be seen in early yellow fever maps. For instance, each map assumes a

bird’s-eye perspective, looking down on the outbreak. The compass symbol

in Figure 2 (Seaman’s map) suggests that the top of the map and toward the

left represents north whereas the compass symbol in Figure 3 (Pascalis’s,

1819 map) indicates that the top right of the map represents north. Symbols

in the top right-hand corner of Jewell’s (1853) map of the South Street

Wharf (see Figure 4) show that north is toward the right and west is toward

the top of the map, most likely because the outbreak spread west and north

from the dock areas. Jewell (1853) also included illustrations of two ships.

The Mandarin is centered at the bottom of the map, emphasizing its impor-

tance as the real cause (to use the interpretive framework of Kress & van

Leeuwen, 1996). A second ship, the Brig Staets Von Brock, is located near

the last case of yellow fever (Jewell, 1853, p. 32) and is shown closer to the

Figure 3. Pascalis’s (1819) map of a yellow fever outbreak near the Old Slip area.Source: National Library of Medicine, History of Medicine Division.




edge and the bottom of the map, which visually downplays its importance.

Jewell clusters most of the cases in the center of the map, emphasizing the

nucleus of the outbreak (again drawing on Kress & van Leeuwen, 1996) as

yellow fever spread up from the Mandarin and the dock areas it occupied.

Pascalis (1819) too included the docks at the bottom of his map (see Fig-

ure 3), which allowed him to place the majority of the cases in the center.

This centering visually emphasizes the area where most of the cases

occurred—as he put it, ‘‘out of 57 cases (the total of them) the enormous

proportion of 34 or 35 originated from that single block’’ (p. 20)—and

de-emphasizes the docks and river area. In his report, he described the over-

all poor sanitary conditions of Old Slip, the location of the outbreak—‘‘This

place has always been the common receptacle of the whole filth of the city’’

(p. 19)—and the specific conditions that may have produced miasma, spe-

cifically ‘‘heat and moisture, exciting a putrid fermentation in the soil, or in

accumulated putrescible materials under or about us’’ (p. 17). Rather than

using ‘‘spots’’ or dots to show individual cases, he included rectangular bars

and boxes (perhaps to visually represent the houses where cases occurred)

Figure 4. Jewell’s (1853) map of a yellow fever outbreak near the South StreetWharf area in Philadelphia. Source: Courtesy of the Historical Medical Library of theCollege of Physicians of Philadelphia.

Welhausen 11



with numbers listed inside the bars to show temporal information. From a

21st-century perspective, Pascalis’s use of shading is not conventional

(the rectangular bars are lighter whereas the city blocks are darker)

because this map predates this visual convention. Nonetheless the map

demonstrates the convention of using shading to differentiate between

visual information.

Conversely, Seaman (1798)—who created two maps of an earlier out-

break also in New York—placed the docks to the right in his representa-

tions. He believed that the outbreak originated from concentrated areas of

garbage and debris near the docks, as shown in his second map (see Figure

2). Like Jewell he placed these areas near the bottom of the map, perhaps to

emphasize the location of the real causes.

The preceding analysis demonstrates that the creators of several early

yellow fever maps—Jewell, Pascalis, and Seaman—made visual choices

in defining and constructing geographic space that would advance their pur-

poses. Rather than being neutral representations of how yellow fever out-

breaks occupied real-world spaces, these maps are fundamentally

rhetorical. Ultimately, the purpose of creating any map is to arrange select

geographic content into an abstracted visual representation that emphasizes

certain features and minimizes others (inclusion and exclusion) in construct-

ing new spatial relationships that advance a particular understanding and

interpretation of that space. As Crampton (2010) stated, ‘‘Maps make reality

as much as they represent it’’ (p. 18). Indeed, these early yellow fever maps

are particularly effective in demonstrating this idea because rather than

revealing the truth about how yellow fever was actually transmitted, they

visually advanced a theory (a hypothesis) of disease causation. Shannon

(1981) observed that Seaman and Pascalis accurately concluded that yellow

fever was not contagious, but in the absence of scientific knowledge about the

disease’s etiology, miasma seemed to be the only other logical explanation.

Because the creators of early disease maps were constrained by these

limitations, they were also invariably limited in terms of the arguments they

could make about disease causation. As Krieger (2011) pointed out,

researchers are shaped by the ‘‘ideas and beliefs of their time’’ (p. 27),

which further highlights the rhetoricity of these early maps. What is possi-

ble to know (or to believe) is controlled by ideology, epistemology, and the

limitations of accepted methodologies. That is, scientific knowledge does

not emerge from neutral, disinterested, open-ended inquiry; rather, it is

shaped by what a particular culture (and researchers within that culture) can

know, believe, and do, as well as by what they believe is possible to know,

believe, and do, at a particular point in time.




Constructing Power and Authority as StatisticalGraphics

Technical communication scholarship has called attention to the rhetoricity

of statistical graphics (see Brasseur, 2004; Dragga & Voss, 2001) and sci-

entific communication (see Gross, 1996; Kuhn, 1996). Yet statistical gra-

phics are particularly powerful rhetorical constructions because they are

simultaneously both visual and scientific forms of communication. These

forms carry the weight of scientific authority within the context of the

often-assumed transparency of visuals, which work together to invoke a

narrative of scientific progress, promote underlying positivist assumptions,

and downplay the ways that these forms work rhetorically to construct

quantitative information. As essentially the visual equivalent of scientific

data, there is still perhaps no other visual genre, with the exception of photo-

graphs and maps, of course, that invokes the notion that visuals are objec-

tive and neutral representations quite like statistical graphics.

Historic yellow fever maps visually invoke this scientific authority and

presumption of visual neutrality. Seaman’s (1798) maps, for instance, did

not prove that miasma causes yellow fever. Rather, they worked alongside

the mounting evidence outlined in his report as well as his previous research

to reveal ‘‘the simple result of the foregoing facts and observations.’’ In his

report, Seaman definitively concluded ‘‘that no Yellow Fever can spread,

but by the influence of putrid ‘effluvia’’’ (p. 331). He also alluded to the

notion that scientific progress is cumulative and continually evolving, draw-

ing on other possible research and knowledge that might emerge from

future investigations:

If I have succeeded, my end is answered, and my trouble fully compensated;

if not, I still gratify myself with the thoughts of having established, with a

considerable degree of accuracy, facts, that may be Useful to some more for-

tunate inquirer. (Seaman, 1798, p. 315)

His final assessment here echoes a familiar appeal to the authority of scien-

tific facts as self-evident. When such facts are carefully weighed and con-

sidered in their entirety, a pattern will emerge from research (such as his)

that reveals the truth.

Similarly, Pascalis’s (1819) map (Figure 3) too draws on scientific

authority. He stated that ‘‘it has evidently been ascertained, that no case

of yellow fever has originated in any part of the city of New-York, except

in the spot or vicinity of Old Slip, of which a correct map is subjoined’’

Welhausen 13



(p. 46). His statement appeals to logical reasoning and the authority of the

map in establishing an accurate representation of the disease. If yellow

fever is contagious, then another infected person somewhere in the city

would had to have caused the outbreak, so the contagion would have ‘‘dif-

fuse[d] its agency in a more equal and diffusible proportion’’ (p. 48). The

map visually proves the accuracy of his assertion because it is ‘‘correct,’’

so some other causal factor must be at work.

Yet while Pascalis’s map may have correctly represented cases in the

Old Slip area, its coverage of the full geographic reach of the outbreak is

not entirely accurate. Koch (2005) explained that Pascalis’s map only

shows fatal yellow fever cases that occurred near the docks when he could

have also shown those that occurred on ships in the nearby harbor; including

this information would have strengthened Pascalis’s overall argument about

the cause of the outbreak but weakened his sanitary reform agenda. By

excluding information from his map that did not support his purposes, Pas-

calis constructed a particular factual reality that maintained a narrative of

progress in identifying the epidemic’s causes.

Constructing Power and Authority ThroughWestern Ideologies

In addition to using visual conventions and drawing on their scientific

authority as statistical graphics, early yellow fever maps also invoked

power by visually promoting underlying ideologies of Western medicine,

often referred to as the biomedical model of medicine. Biomedicine is

Western medicine, Segal (2005, p. 23) explained, and it replaced humorism

and its holistic approach to health with ‘‘the medical body’’ that emerged

with the 19th-century institutionalization of medicine that Foucault theo-

rized (Segal, 2005, p. 26). Biomedicine was solidified in the late 19th cen-

tury with the discovery of germ theory and is now characterized by four

core assumptions outlined by sociologist Elliott Mishler (1981): ‘‘(1) the

definition of disease as deviation from normal biological functioning; (2)

the doctrine of specific etiology; (3) the conception of generic diseases, that

is, the universality of a disease taxonomy; and (4) the scientific neutrality of

medicine’’ (p. 3). This last assumption, scientific neutrality, is discussed in

the previous section within the context of statistical graphics.

Disease maps visually reinforce Mishler’s (1981) first assumption of

‘‘disease as deviation from normal biological functioning’’ by dividing (and

marking) the geographic space of an outbreak into binary categories,

namely, diseased and not diseased. Because thematic mapping first arose




in Europe (see Friendly & Denis, 2006; Funkhouser, 1937; Robinson,

1982), from their inception, disease maps as well as other thematic maps,

reflected Western cultural assumptions about space, Trieb (1980)

explained, ‘‘as something which can be measured, divided, sub-divided and

multiplied’’—that is, as a concept that can be quantified (p. 5). This division

between diseased and not diseased then provides the initial framework for

controlling that space.

Indeed, early yellow fever maps visually divide this space. While Sea-

man’s (1798) second map (see Figure 2) marks polluted areas near the

docks and uses dots to identify the location of individual cases, Pascalis’s

(1819) map (see Figure 3) includes mostly rectangular bars with one or

more numbers listed inside the bars to show temporal information. In this

map, the unshaded streets and rectangular bars create a clear division

between diseased and not diseased space when positioned next to the

shaded city blocks. In Barton’s (1857) map (see Figure 5), created more

than 50 years after Seaman’s maps, this binary division is even more pro-

nounced. In contrast to Seaman’s and Pascalis’s maps, which show actual

cases, Barton’s map highlights areas that could presumably become dis-

eased space. Specifically, his map shows ‘‘disturbances of the soil’’ (thin

black lines) and ‘‘Nuisances,’’ areas such as ‘‘cemeteries, Slaughter

houses . . . Open basins and unfilled lots’’ (thick black lines), as explained

on the map. Unlike Pascalis, Barton uses shading in ways that are imme-

diately understandable to 21st-century viewers—areas at risk for spreading

miasma are clearly identifiable through the now-established visual conven-

tion of greater density equaling more disease (and potential disease).

Mishler’s (1981) second assumption, ‘‘the doctrine of specific etiology,’’

is the notion that the specific cause of a disease or illness can be clearly iden-

tified. From a 21st-century perspective, this notion seems obviously useful

and necessary. To effectively treat an illness, physicians must accurately

diagnose the specific condition that caused it. In contrast to humorism, which

proposed that health was defined by a balance between the four bodily

humors—blood, phlegm, black bile, and yellow bile—specific etiology

clearly supports a biomedical model of disease and health. Humorism also

held that illness was attributed to an imbalance in humors; thus, treating ill-

ness involved correcting this internal imbalance. From a humoral perspective,

then, attempting to identify specific disease markers outside the context of the

relationships between the humors would not have advanced disease preven-

tion because disease was believed to be caused by internal factors.

Disease maps visually reinforce the biomedical model through specific

etiology by mapping single variables of interest—cases of a particular

Welhausen 15



disease or illness, for instance—in a particular geographic region. Specific

etiology can be seen in the oldest surviving disease maps such as the 1694

Bari plague map:

Embedded in the map is a tight argument linking the history of plague’s pre-

vious occurrences (the basis for containment), the limits of medical science

(no treatment but a general etiology), and the social structure of the greater

community (civil, military, medical and religious). (Koch, 2005, p. 23)

Early yellow fever maps too reflect specific etiology. The creation of these

maps promotes the idea that disease can be described and understood

through the temporal (e.g., indicated by numbering cases, as in Figures 2

and 3) and spatial progression of each outbreak in its respective geographic

locations. Koch (2005) observed that Pascalis’s (1819) map argued for

‘‘cause and effect relationships’’ based on ‘‘simple proximity’’ (p. 37); cer-

tainly Seaman’s (1798, see Figure 2) and Jewell’s (1853, see Figure 4) maps

too rely on this visual strategy. Shannon (1981) explained that Seaman

Figure 5. Barton’s (1857) sanitary map of New Orleans. Source: Courtesy of theHistorical Medical Library of the College of Physicians of Philadelphia.




intended his first map (not shown) ‘‘to be a demonstration of cause and

effect’’ (p. 224) through his visual representations of the spatial relation-

ships between the distribution of the disease and what Seaman determined

to be the causal factors. Visually, these early maps reinforce the idea that if

users of the map could better understand how a disease occupies and moves

through space, place, and time, then they could also more effectively under-

stand the underlying causal factors.

Historic yellow fever maps also demonstrate Mishler’s (1981) third

assumption, ‘‘the universality of a disease taxonomy,’’ which refers to the idea

that ‘‘disease symptoms and processes are expected to be the same in different

historical periods and in different cultures and societies’’ (p. 9). In early yellow

fever maps, disease and illness become static rather than dynamic entities that

change as an outbreak moves through space and time. Koch (2011) observed

that Seaman ‘‘assumed all yellow fever outbreaks were the same disease, and

further, he [Seaman] implied that yellow fever everywhere (Barbados, Boston,

Philadelphia, New Orleans, and on) was the same’’ (p. 87).

Embedded within this assumption of universality are two other assump-

tions: predictability and prevention. If all outbreaks of a particular disease

are the same, that is, they follow a similar temporal (and spatial) progres-

sion of symptomatology and outcomes, then knowing about the character-

istics of an outbreak that occurred in the past can be used to predict (and

subsequently prevent) future outbreaks. Barton’s (1857) sanitary map

demonstrates this idea by identifying areas where the miasma that caused

yellow fever might develop in the future. Pinpointing these locations

allowed Barton as well as other users of the map to enact metaphorical as

well as real-world control over the space by seeing it as something that

could be understood, managed, and ultimately fixed. Kimball (2006) made

a similar point in his treatment of the visual rhetoric of Charles Booth’s pov-

erty maps, suggesting that, in part, Booth’s maps communicate the idea that

they represent ‘‘a fixable real London’’ (p. 361). In promoting the notion

that physical space can be controlled in this way, disease maps also advance

a narrative of scientific progress. If the spatial and temporal distribution of

disease can be understood, better containment methods can be developed,

which will ideally result in fewer outbreaks.

Constructing Power and Authority in ContemporaryYellow Fever Mapping

The controlling metaphor of Western medicine is perhaps, as Segal (2005)

put it, ‘‘the body is a machine,’’ attended to in terms of ‘‘working and

Welhausen 17



nonworking parts’’ (p. 121). But the controlling metaphor of modern-day

epidemiology, with its emphasis on managing epidemic disease in popula-

tions, is containment, and containment is achieved by enacting real-world

control over diseased space. Historic yellow fever maps enacted this control

metaphorically through their visual choices, by drawing on their scientific

authority as statistical graphics and by visually invoking Western ideologies

about disease, illness, and health. Today these strategies remain largely

unchanged, which can still be seen in a yellow fever map (Figure 6) show-

ing areas at risk for the disease in Africa.

Much like early yellow fever maps, this contemporary map uses perspec-

tive to assume metaphorical control over the space it represents by looking

down on at-risk and not at-risk areas through an all-knowing point of view.

The most important information—at-risk countries—is also placed in the

center of the map, visually calling attention to these places.

Color and shading too are significant visual features. The map uses

yellow to communicate a literal semiotic message (yellow shading equals

yellow fever) as well as a metaphoric message—the warm color yellow

visually emphasizes the at-risk areas in contrast to the gray not at-risk areas.

While color is not used in the historic yellow fever maps discussed earlier

Figure 6. Areas at risk for yellow fever in Africa (Jentes et al, 2011).




(possibly due to technological limitations), some early cholera maps such

as Rothenburg’s 1836 map of an outbreak in Hamburg (see Koch, 2011,

pp. 130–131) and Shapter’s 1832 map of an outbreak in Exeter (see Koch,

2011, pp. 157–159), used red to show increasing density and ‘‘the greater or

lesser strength of the epidemic,’’ as Rothenburg put it (cited in Robinson,

1982, p. 171), establishing a historic precedent for using color to commu-

nicate the density of diseased space.

Using shading to signify increasing quantity is now a conventional fea-

ture of most disease maps, which can be seen in many historic yellow fever

maps, such as Barton’s (1857) sanitary map as well as the cholera maps

mentioned previously. Yet because the number of reported cases for yellow

fever over the past 50 years is extremely low (see World Health Organiza-

tion, 2014a), these contemporary maps use the opposite visual strategy—

that is, lighter density indicates at-risk areas; darker density indicates not

at-risk areas. The contrast between these light and dark areas also creates

a visual binary between at-risk areas and not at-risk areas, with the darker

areas signifying spaces that have been contained and the lighter areas sig-

nifying areas that still need to be contained.

Contemporary maps also advance underlying Western assumptions and

ideologies about disease and illness through their use of color. For instance,

the yellow shading (signifying yellow fever) in the map shown in Figure 6

marks diseased space as different from the ‘‘neutral’’ dark-gray space,

visually reinforcing the idea that the yellow, at-risk space is ‘‘deviation’’

from the normal. Further, the visual representation of each of these two

spaces (yellow and dark gray) is uniform, suggesting ‘‘a universal disease

(and not diseased) taxonomy’’ (Mishler, 1981, p. 3)—that is, all at-risk and

all not at-risk areas are the same.

This contemporary map too advances a narrative of scientific progress,

which can be seen by considering the increasing geographic range of the

yellow fever maps discussed throughout this article. The earliest maps cre-

ated by Seaman (1798) and Pascalis (1819) show just a few city blocks.

Thirty years after Pascalis’s map, Jewell’s (1853) map expands geographic

coverage to a neighborhood (the South Street Wharf area in Philadelphia,

see Figure 4). Shortly thereafter, Barton’s (1857) map shows the entire city

of New Orleans (see Figure 5). The contemporary map shown in Figure 6

encompasses the entire continent of Africa. This brief historic comparison

demonstrates that as geographic coverage of yellow fever has expanded, the

density of diseased space has also correspondingly decreased.

Indeed, after the invention of the yellow fever vaccine in the 1930s and

subsequent mass vaccination efforts (see Rogers et al., 2006; World Health

Welhausen 19



Organization, 2014b), the disease is no longer the major public health con-

cern in many parts of the world that it was in the 19th century. Yet the dis-

ease remains endemic in 44 African and South American countries (World

Health Organization, 2008). At the same time, because the spread of this

disease has been largely contained, contemporary maps no longer show

cases (i.e., actual diseased space) because there are so few. Rather, they

show areas at risk for becoming diseased space, thus further advancing

an overall narrative of scientific progress by encompassing increasingly

larger areas, demonstrating global containment.

The Biomedical Model and Implications for DiseaseMapping in the 21st Century

Today public health is global health, and researchers at the local, state,

national, and international level routinely coordinate disease prevention and

health promotion efforts across large geographic areas. Within this context,

disease mapping continues to be a powerful data visualization tool, and new

technologies over the past few decades such as geographic information sys-

tems have allowed researchers to create increasingly sophisticated visual

representations (see also Lawson & Kleinman, 2005). Thus, understanding

the ways in which these representations visually construct knowledge about

how disease is situated in geographic space has significant implications for

contemporary public health decisions.

The earliest surviving disease maps (see Figures 2 and 3) established

visual strategies for enacting metaphorical control over diseased space in

ways that promote Western ideologies about medicine that can still be seen

in contemporary maps (see Figure 6). Further, these ideologies often frame

how Western cultures conceive of disease, illness, and health in the 21st

century. By positioning disease and illness as other, as a deviation, as Mish-

ler (1981, p. 3) put it, from normal human experience, Western medicine

works to advance the notion that disease and illness can be managed, con-

trolled, and more important, conquered. Indeed it is difficult not to use the

language of conquest when describing disease and illness in Western cul-

tures in the 21st century because this perspective is also reinforced through

language in the form of war metaphors (see Segal, 2005).

Yet many cultures see disease and illness differently, and some read

and use maps in ways that differ dramatically from those in Western cul-

tures (see Turnbull’s 1989 discussion of aboriginal maps). Thus, if global

public health practices and decisions are shaped only by the ideologies

that underlie Western medicine, we may miss opportunities to see other




problem-solving approaches as well as benefit from non-Western

perspectives.

Segal (2005) explained that Western medicine emerged in the 16th and

17th centuries after a shift occurred in medical practice from attending to

the ‘‘body as a whole’’ (p. 24), which characterized humoral theory, to

attending to the ‘‘medical body’’ (p. 26). This move from the ‘‘diseased per-

son’’ to the ‘‘disease community’’ (p. 27), as Segal put it, has been critiqued

by Foucault (1973) as leading to the institutionalization and mechanization

of Western medicine. Indeed, the perspective advanced by Western medi-

cine can reduce disease, illness, and even health to disembodied things that

exist outside of bodily experiences. Many diseases are caused by external

agents—viruses and bacteria, for instance—but the physical state of being

sick or healthy is embodied. The ideologies that underlie Western medicine,

however, can work to downplay and mask the notion that illness is a lived

bodily experience.

This discussion has highlighted several limitations of Western medicine.

Yet the ideologies that tend to underlie Western medicine have also offered

a way of thinking about disease, illness, and health that facilitated the move

toward our modern-day public health perspective with its emphasis on dis-

ease prevention and health promotion in populations. The history of public

health can be traced back to antiquity (see Rosen, 1993), but public health

was only formally recognized as a discipline in the mid-19th century (Krie-

ger, 2011), during a time when the evolution of contemporary statistical

graphics had entered a ‘‘golden age,’’ as Friendly (2008) described it.

Patients have individual experiences with sickness and health, but epi-

demics affect populations. And attending to an epidemic requires adopting

the broader perspective that Western medicine facilitates. Western medi-

cine allows researchers to see epidemics as occurring within populations

and to see disease and illness as measurable and quantifiable—that is, as

information that can be used to draw generalizable conclusions, which can

then lead to informed public health decisions.

The data visualization techniques used in the early yellow fever maps

illustrate this shift from an individual to a group-based perspective. Seaman

(1798, see Figure 2) and Pascalis (1819, see Figure 3), for instance, each

include a single dot and a number on their maps representing individual

cases (patients). Each number also correlates with a short description of

each patient’s symptoms in the body of the report and often the time frame

for the development of symptoms and the progression of the illness. Thus,

the more detailed qualitative information in the report is separated from the

less detailed and quantifiable information shown in the map. Similarly,

Welhausen 21



Jewell (1853) included detailed descriptive information. But unlike Seaman

and Pascalis, he used two data visualization techniques that further quantify

the information about this particular outbreak: his map, which includes

cases and numbers, and a table next to the map, which visually aggregates

much of his descriptive information.

From a 21st-century perspective, much of the descriptive patient infor-

mation in these reports probably seems unnecessary. But this level of detail

probably served at least two purposes. First, without definitively knowing

how yellow fever was actually spread or having the scientific knowledge

to accurately diagnose the disease, these descriptions may have been neces-

sary to persuade readers that the epidemic had indeed been caused by yel-

low fever and not another illness with similar symptomology. Second,

considering the ways in which these three maps (see Figures 2, 3, and 4)

attempt to group quantitative and qualitative information both textually and

graphically reveals the transition to an increasingly abstracted representa-

tion of quantifiable information. Once researchers began to think about con-

trolling disease from an epidemiological perspective—that is, in terms of

how disease affects populations and not just individual patients—they could

then use this quantitative information to develop specific theories of disease

etiology. These theories could then be used to formulate hypotheses about

disease spread and ultimately used to prevent future outbreaks.

This shift in thinking facilitated by Western medicine toward a

population-based perspective may seem to reject the validity of patients’

individual lived bodily experiences. But instead it offers a consolidated ver-

sion of individualized experience, allowing researchers to understand dis-

ease, illness, and health in ways that they would not, indeed could not,

have otherwise been able to understand. More specifically, the very notion

that epidemic disease (or any disease) might be contained would simply not

have been possible without this shift in perspective. The earliest disease

maps show this change in thinking, which continues to shape how we con-

ceive of disease, illness, and even health today.

The goal of critical cartography and modern-day geographic information

systems, Crampton (2010) explained, ‘‘is not to over-turn this [scientific]

way of knowing . . . but to ask how it has come to be so powerful . . . to

ask what the implications are of this knowledge and whether or not alterna-

tive ways of knowing are possible’’ (pp. 39–40). Further, he suggested that

‘‘one way to challenge [these] orders of knowledge is by putting them into

historical perspective’’ (p. 17). By conducting a selected history of yellow

fever mapping, this article seeks to do just that—more specifically, to illus-

trate the ways in which historic disease maps established a visual precedent




for invoking metaphorical control over diseased space, the ways in which

the ideologies of Western medicine reinforced this control, and the ways

in which these maps shaped the visual conventions of disease mapping that

are still in practice today.

Mapmaking, Jacob (1996) explained, is about creating ‘‘possibilities’’:

Every map displays a specific world; so does it display the world as it is, as it

was, as it will be, as it could be, or as it should be? Each of these possibilities

implies a specific view of the map and specific intellectual operations. (p. 195)

Disease maps show a snapshot of a particular epidemic in space and time at

a particular point in the past. But while these maps document the previous

state of an epidemic, they are not really about understanding the past. Dis-

ease maps are created to better understand the future. These data visualiza-

tions tell us about what happened, but more important, they tell us about

what might happen—the world as it might be or could be (to use Jacob’s

wording). They tell us what is possible to know and believe about the future,

which in turn allows us to have some sense of power, authority, and ulti-

mately control over that future.

Authors’ Note

Figure 6 reprinted from Lancet Infectious Diseases, 11, Jentes, E. S., Poumerol, G.,

Gershman, M. D., Hill, D. R., Lemarchand, J., Lewis, R. F., Staples, J. E.,

Tomori, O., Wilder-Smith, A., & Monath, T. P., for the informal WHO Working

Group on Geographic Risk for Yellow Fever. The revised global yellow fever risk

map and recommendations for vaccination, 2010: consensus of the Informal WHO

Working Group on Geographic Risk for Yellow Fever, 622–32, (2011), with permis-

sion from Elsevier.

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research,

authorship, and/or publication of this article.

Funding

The author received no financial support for the research, authorship, and/or pub-

lication of this article.

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Author Biography

Candice A. Welhausen is an assistant professor of technical communication at the

University of Delaware. Her research focuses on visual rhetoric in two areas: data

visualizations in the field of public health and epidemiology, and pedagogical

practice.

Welhausen 27


http://apps.who.int/immunization/topics/yellow_fever/en/index.html

http://apps.who.int/immunization/topics/yellow_fever/en/index.html

http://www.who.int/csr/disease/yellowfev/impact1/en/

http://www.who.int/csr/disease/yellowfev/massvaccination/en/

http://www.who.int/csr/disease/yellowfev/massvaccination/en/


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